Triple
T16761764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Emile Anka |
E407360
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Andrew Emile Anka |
E407360
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Andrew Emile Anka | Statement: [Andrew Emile Anka, name, Andrew Emile Anka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Emile Anka Context triple: [Andrew Emile Anka, name, Andrew Emile Anka]
-
A.
Andrew Emile Anka
chosen
Andrew Emile Anka is one of the children of Canadian-American singer, songwriter, and actor Paul Anka.
-
B.
George Tutuska
George Tutuska is an American rock drummer best known for his early work and recordings with the Goo Goo Dolls before their mainstream breakthrough.
-
C.
Edward Zorinsky
Edward Zorinsky was a U.S. Senator from Nebraska and former mayor of Omaha known for his moderate Democratic politics and service in the late 20th century.
-
D.
Louis Bakanowsky
Louis Bakanowsky was an American architect best known as a founding partner of the influential design firm Cambridge Seven Associates.
-
E.
George Kozmetsky
George Kozmetsky was an American technology entrepreneur, investor, and educator best known as a co-founder of Teledyne and a major figure in fostering innovation and high-tech industry growth.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d8839174188190909f190097207065 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3abed67f88190afb1d392ff01a5e7 |
completed | April 18, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52d077081908080c61da67e0032 |
completed | May 10, 2026, 3:33 p.m. |
Created at: April 10, 2026, 5:21 a.m.